Noise-enhanced information systems

Hao Chen, Lav R. Varshney, Pramod K. Varshney

Research output: Contribution to journalArticlepeer-review

58 Scopus citations


Noise, traditionally defined as an unwanted signal or disturbance, has been shown to play an important constructive role in many information processing systems and algorithms. This noise enhancement has been observed and employed in many physical, biological, and engineered systems. Indeed stochastic facilitation (SF) has been found critical for certain biological information functions such as detection of weak, subthreshold stimuli or suprathreshold signals through both experimental verification and analytical model simulations. In this paper, we present a systematic noise-enhanced information processing framework to analyze and optimize the performance of engineered systems. System performance is evaluated not only in terms of signal-to-noise ratio but also in terms of other more relevant metrics such as probability of error for signal detection or mean square error for parameter estimation. As an important new instance of SF, we also discuss the constructive effect of noise in associative memory recall. Potential enhancement of image processing systems via the addition of noise is discussed with important applications in biomedical image enhancement, image denoising, and classification.

Original languageEnglish (US)
Article number6877641
Pages (from-to)1607-1621
Number of pages15
JournalProceedings of the IEEE
Issue number10
StatePublished - Oct 1 2014


  • Noise-enhanced signal processing
  • Stochastic facilitation (SF)
  • Stochastic resonance (SR)

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


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